Properties of the aftershocks sequences of the 2000 and 2002 earthquakes in Aksehir-Afyon graben,west-central Anatolia,Turkey

The b-value of the Gutenberg–Richter’s frequency–magnitude relation and the p-value of the modified Omori law, which describes the decay rate of aftershock activity, were investigated for more than 500 aftershocks in the Aksehir-Afyon graben (AAG) following the 15 December 2000 Sultandagi–Aksehir and the 3 February 2002 Çay–Eber and Çobanlar earthquakes. We used the Kandilli Observatory’s catalog, which contains records of aftershocks with magnitudes ≥2.5. For the Çobanlar earthquake, the estimated b-values for three aftershock sequences are in the range 0.34 ≤  b ≤ 2.85, with the exception of the one that occurred during the first hour (4.77), while the obtained p-values are in the range 0.44 ≤ p ≤ 1.77. The aftershocks of the Sultandagi earthquake have a high p-value, indicating fast decay of the aftershock activity. A regular increase of b can be observed, with b < 1.0 after 0.208 days for the Çay–Eber earthquake. A systematic and similar increase and decrease pattern exists for the b- and p-values of the Çobanlar earthquakes during the first 5 days.     

Clustering current climate regions of Turkey by using a multivariate statistical method

In this study, the hierarchical clustering technique, called Ward method, was applied for grouping common features of air temperature series, precipitation total and relative humidity series of 244 stations in Turkey. Results of clustering exhibited the impact of physical geographical features of Turkey, such as topography, orography, land–sea distribution and the high Anatolian peninsula on the geographical variability. Based on the monthly series of nine climatological observations recorded for the period of 1970–2010, 12 and 14 clusters of climate zones are determined. However, from the comparative analyses, it is decided that 14 clusters represent the climate of Turkey more realistically. These clusters are named as (1) Dry Summer Subtropical Semihumid Coastal Aegean Region; (2) Dry-Subhumid Mid-Western Anatolia Region; (3 and 4) Dry Summer Subtropical Humid Coastal Mediterranean region [(3) West coast Mediterranean and (4) Eastern Mediterranean sub-regions]; (5) Semihumid Eastern Marmara Transition Sub-region; (6) Dry Summer Subtropical Semihumid/Semiarid Continental Mediterranean region; (7) Semihumid Cold Continental Eastern Anatolia region; (8) Dry-subhumid/Semiarid Continental Central Anatolia Region; (9 and 10) Mid-latitude Humid Temperate Coastal Black Sea Region [(9) West Coast Black Sea and (10) East Coast Black Sea sub-regions]; (11) Semihumid Western Marmara Transition Sub-region; (12) Semihumid Continental Central to Eastern Anatolia Sub-region; (13) Rainy Summer Semihumid Cold Continental Northeastern Anatolia Sub-region; and (14) Semihumid Continental Mediterranean to Eastern Anatolia Transition Sub-region. We believe that this study can be considered as a reference for the other climate-related researches of Turkey, and can be useful for the detection of Turkish climate regions, which are obtained by a long-term time course dataset having many meteorological variables.     

An Iron Meteorite from Akyumak

Abstract— The microstructure of an iron meteorite which fell near Akyumak, East Anatolia, Turkey on 2 August 1981 has been examined and its composition determined. The Ni content is 7.7% and kamacite bandwidth is 0.32 ± 0.06 mm. The kamacite contains Neumann bands and some daubreelite inclusions. Taenite and plessite account for about 45 to 50% of the metal; finger, cellular and net plessite are observed. Gallium (1.9 ppm), Ge (< 40 ppm) and Ir (1.81 ppm) were determined by neutron activation. The microstructural observations and chemical data show Akyumak to be a fine octahedrite and a member of group IVA.     

Predicting rainfall intensity using a genetic algorithm approach

A genetic algorithm rainfall intensity (GARI) model has been developed and used to predict the intensities for given return period. It is a one‐step solution procedure that may not require any mathematical transformation. The problem formulation is given and the genetic algorithm solution of the problem is presented. The results show that the proposed GARI model can be used to solve the rainfall intensity–duration–frequency relations with lowest mean‐squared error between measured and predicted intensities. Predicted intensities are in good agreement between measured and predicted values for given return periods. Copyright © 2006 John Wiley & Sons, Ltd.     

Comparison of missing value imputation methods in time series: the case of Turkish meteorological data

This study aims to compare several imputation methods to complete the missing values of spatio–temporal meteorological time series. To this end, six imputation methods are assessed with respect to various criteria including accuracy, robustness, precision, and efficiency for artificially created missing data in monthly total precipitation and mean temperature series obtained from the Turkish State Meteorological Service. Of these methods, simple arithmetic average, normal ratio (NR), and NR weighted with correlations comprise the simple ones, whereas multilayer perceptron type neural network and multiple imputation strategy adopted by Monte Carlo Markov Chain based on expectation–maximization (EM-MCMC) are computationally intensive ones. In addition, we propose a modification on the EM-MCMC method. Besides using a conventional accuracy measure based on squared errors, we also suggest the correlation dimension (CD) technique of nonlinear dynamic time series analysis which takes spatio–temporal dependencies into account for evaluating imputation performances. Depending on the detailed graphical and quantitative analysis, it can be said that although computational methods, particularly EM-MCMC method, are computationally inefficient, they seem favorable for imputation of meteorological time series with respect to different missingness periods considering both measures and both series studied. To conclude, using the EM-MCMC algorithm for imputing missing values before conducting any statistical analyses of meteorological data will definitely decrease the amount of uncertainty and give more robust results. Moreover, the CD measure can be suggested for the performance evaluation of missing data imputation particularly with computational methods since it gives more precise results in meteorological time series.     

Observed climate variability and change in Urmia Lake Basin, Iran

This paper analyzes climate variability and change in the Urmia Lake Basin, northwest of Iran. Annual average of the following data time series has been analyzed by statistical methods: dry bulb temperature, maximum and minimum temperature, precipitation, and number of rainy and snowy days. We have also used mean monthly temperature and precipitation data for analysis of drought spells for the period 1964–2005 to find out whether fluctuations in the lake level are attributable to natural drought. Our results indicate that mean precipitation has decreased by 9.2 % and the average maximum temperature has increased by 0.8°C over these four decades. The seasonal changes are particularly visible in winter and spring. Results of the Palmer Drought Severity Index show that on average, drought episodes have hit the Urmia Lake Basin every 5 years and most of them reached severe levels, but recent droughts have become more intense and last longer.